The cloud computing environment is an enhancement to the predecessor grid environment, whereby multiple grids and other computation resources may be further abstracted by a cloud layer, thus making disparate devices appear to an end-consumer as a single pool of seamless resources. These resources may include such things as physical or logical compute engines, servers and devices, device memory, storage devices.
As enterprise storage clouds grow bigger in size, it becomes increasingly difficult to debug performance issues. Specifically, workload data may be distributed across multiple redundant components, and a single input/output (I/O) request may span multiple tiers of software and hardware components. When a storage workload experiences performance issues, it is quite challenging to accurately pinpoint the problematic node(s) (e.g., those that are causing the issues). Existing approaches rely upon methods that analyze logs from individual components. Such an approach may not readily identify a route cause of performance issues and may not scale well with respect to ESS capacity.